Category Archives: Inequality

by Erik Bengtsson (Lund) and Daniel Waldenström (Paris School of Economics and CEPR)

Abstract – This article studies the long-run relationship between the capital share in national income and top personal income shares. Using a newly constructed historical cross-country database on capital shares and top income data, we find evidence on a strong, positive link that has grown stronger over the past century. The connection is stronger in Anglo-Saxon countries, in the very top of the distribution, when top capital incomes predominate, when using distributed top national income shares, and when considering gross of depreciation capital shares. Out of-sample predictions of top shares using capital shares indicates several cases of over- or underestimation.

Until recently, many academic economists would react sceptically to the idea of income inequality. It is absolute poverty what matters, they would argue, and sustained growth is the answer. It would be misled, however, to conclude the only lately has inequality become part of the economists’ agenda. Actually inequality has always been present in economists’ preoccupations. Its symptoms have varied, as social sensitivity to inequality has changed over time. Classical economists identified personal income distribution with the functional income distribution as inequality largely depended on the gap between average incomes of capital and labour. This is clearly exposed in David Ricardo’s famous passage in which he noted that the explaining the distribution of “the produce of earth (…) among (…) the proprietor of the land, the owner of the stock or capital (…) and the labourers” is the main purpose of political economy. In the early 20th century, as the share of skilled workers in the labour force was increasing, Simon Kuznets noted the dispersion of labour incomes and highlighted its role as a driving force of income inequality. At the turn of the century, the increase in the concentration of income at the top of the distribution has renewed the concern about inequality as the contributions of the late Sir Tony Atkinson, Thomas Piketty, and their collaborators evidence. It is in this context where Eric Bengtsson and Daniel Waldeström’s important contribution should be read.

The purpose of Bengtsson and Waldeström was to the test the existence of a long run connection between the functional and the personal distribution of income. As economic historians they find no reason to assume the relationship would be stable over time and across countries since many other dimensions (technology, institutions, personal incomes composition, …) will impinge on it.

Their analytical framework is the decomposition of income inequality, using the coefficient of variation, into wages and capital income dispersion, factor shares, and the correlation between capital and labour income, from which a link between capital share and income inequality is predicated. More specifically, a positive association between the two metrics is hypothesised: as capital returns are more unevenly distributed than those accruing to labour, a rise in the share of capital in national income would result in an increase in personal income inequality.

Once their hypothesis is defined, they deal with the data. On the basis of capital returns and GDP, mostly derived from previous scholarly work, they put together a reasonably homogeneous dataset on capital shares, that is, the ratio of capital incomes (interest, profits, dividends, and realized capital gains) to national income for 21 countries (mostly present-day OECD countries) since 1900. Capital returns are computed form the income side of historical national accounts, which raises the challenge of how to distribute mixed incomes (those of self-employed) between capital and labour. The so called labour method that attributed to the self-employed a labour income equal to that of the average employee in each specific sector of economic activity is the usual approach. Then, they choose income concentration at the top of the distribution as a measure of personal income distribution, since alternative metrics such as the Gini coefficient are not available on yearly basis for their country sample and time span. The dataset on the share of income accruing to the 10, 1, and 0.1 top per cent derives from the World Inequality Database (https://wid.world/wid-world/).

The approach to test the association between personal and functional income distribution is panel regression analysis, in which a log-linear relationship is predicated between top income shares, as dependent variable, and the net (gross) capital share, so the latter’s parameter represents the elasticity of income concentration (inequality) with respect to the capital share. In addition to the baseline equation, they also compute more complex models which include control variables (level of development, proxied by GDP per head; structural change, by the agricultural labour share; relevance of private capital by stock marker capitalisation; and size of the public sector, by the government spending to GDP ratio) country fixed effects, and a linear time trend. The overall view of all countries over the 20th century is complemented by a breakdown by epoch (pre World War II, 1950-80, and 1980-2015) and type of countries (three clubs, the Anglo-Saxon, the Scandinavian, the Western European).

Their main finding is a robust association between top income shares and capital shares over the long run, that results in a high elasticity of income inequality with respect to the capital share that declines when specific periods (1950-1980 and 1980-2015) are considered. Thus, a 10 per cent rise in the net capital share is corresponded by an almost similar increase in income concentration at the top. It is worth noting, however, the lower elasticity –and statistical significance- found for the pre-World War II era. When more complex models, including covariates, are used the fit of the regressions increases but reduces the coefficient for the capital share that, nonetheless, still holds up. The association becomes stronger as top incomes shares are restricted to the 0.1 per cent and a possible explanation is that these mainly correspond to capital earners.

The authors also explore the extent to which capital incomes at the top of the distribution account for the association between top income shares and the capital share. They confirm previous findings suggesting that capital incomes predominate in the incomes of the top earners and increase within the income top. However, the authors find that high-paid salaried employees have been replacing capital earners at the very top of the distribution. In any case, the association between top income share and the capital share is stronger when capital rather than wage or total top incomes are considered.

1913: The wealthy man profits from the sweat of the worker. The cartoon is titled ‘The Reflection’ and the capitalist exclaims ‘I’m a self-made man, look at me’. (Photo by Hulton Archive/Getty Images)

The paper concludes with the authors addressing the crux of the matter, is the capital share a good predictor of inequality? In order to do it, they re-run panel regressions leaving aside the country whose inequality is to be predicted. The results are positive in general, but the authors acknowledge that capital shares are not perfect predictors of concentration at the top of the distribution, to which one may add that top income shares are neither a precise measure of personal income inequality.
This thought-provoking paper raises some reflections. Would not it more intuitive the framework proposed by Milanovic (2005) than the authors’ breakdown of the coefficient of variation? Milanovic decomposes inequality into between-group and within-group inequality. In a similar scenario, with only two groups: proprietors, to whom capital (and land) incomes accrue, and workers who receive the returns to labour, personal income inequality results from both the gap between average incomes of capital and labour (that is, a metric that captures the functional distribution of income) and the dispersion of incomes within both capital owners and workers.

A reference to top income shares shortcomings is missing. Uncritically assuming it is a good proxy of personal income distribution neglects that fact that although top income share satisfies axioms of income scale independence, principle of population, and anonymity only weakly does the Pigou-Dalton transfer principle. Moreover, it is silent on how inequality evolves at the bottom of the distribution.

Some of the results could have been explored more. For example, their finding of a lower elasticity of income inequality with respect to the capital share in the pre-World War II era (that is also found when the Ginis is used as dependent variable) deserves further examination. On the one hand, it seems at odds with the inference of a much higher association between income inequality and the capital share in earlier phases of economic development, as between-group inequality (the average capital incomes to labour incomes ratio) has a larger weight in total personal inequality (the dispersion of capital and labour incomes is presumably lower). On the other, a potential explanation would be the increasing dispersion of factor returns –wages, in particular- in the early 20th century, a finding consistent with Kuznets’ focus on the rise of skilled labour and rural-urban migration.

Another neglected issue (somehow a paradox given the authors’ background) is why income concentration at the top and the net capital share are not associated in the Nordic countries since 1980.

The avenues for research the paper opens deserved more detailed consideration. It is true that in the last section the authors address the issue of how good a prediction of personal inequality the capital share is. However, an obvious extension would be to use the capital share as a proxy for income inequality prior to the early 20th century, when hardly any data on top income shares are available and other measures of inequality such as the Gini are rare.

The paper is worth reading as it represents an ambitious and successful project to deal with income inequality over space and time. Moreover, a most valuable online appendix that complements the freely accessible dataset provided by the authors’ webpage accompanies the paper.

Abstract: Populism may seem like it has come out of nowhere, but it has been on the rise for a while. I argue that economic history and economic theory both provide ample grounds for anticipating that advanced stages of economic globalization would produce a political backlash. While the backlash may have been predictable, the specific form it took was less so. I distinguish between left-wing and right-wing variants of populism, which differ with respect to the societal cleavages that populist politicians highlight. The first has been predominant in Latin America, and the second in Europe. I argue that these different reactions are related to the relative salience of different types of globalization shocks.

Populism has been at the front of news headlines for a while now. Whether it was the controversial campaign for Brexit led by Nigel Farage from the United Kingdom Independence Party (UKIP) and Boris Johnson from the Conservative Party in Great Britain, or the equally controversial campaign and victory of Donald Trump in the recent United States elections, the rise of anti-immigrant and anti-European political parties in countries like France, Greece, and Spain, the so called “anti-imperial Castro-Chavist” movements and governments in Venezuela, Bolivia, and Ecuador, or the opposition of the Democratic Center Party (a right-wing political agrupation led by ex-president Alvaro Uribe Velez) to the peace treaty in Colombia, populism is back and very strong, and according to the author, it is here to stay for the foreseeable future.

Dani Rodrik combines the use of economic history and economic theory to analyze the recent surge of these populist movements across Europe and America (see a blog-post version of the paper on VOX here). The main argument of the paper is that “advanced stages of globalization are prone to populist backlash” and the specific form populism takes will depend on the different societal cleavages that politicians can exploit to promote anti-establishment movements. There will be a tendency for left-wing populism when “globalization shocks take the form of trade, finance, and foreign investment”. The opposite will happen when “the globalization shock becomes salient in the form of immigration and refugees”.

Rodrik first presents a rather short summary of what economic history has to say about the appearance of populism during the first globalization era. He points out to the abolition of the Corn Laws in Britain in 1846 as the origin of a series of commercial treaties that, combined with the Gold Standard and free mobility of capital and people, made the world almost as globalized as it is today. Nonetheless, the decline of agricultural prices in the 1870s and 1880s motivated an increase in agricultural tariffs in almost all of Europe, and later on, the United States instituted a series of acts to reduce immigration from several countries. Moreover, Rodrik argues that the first self-consciously populist movement appeared in the US during the 1880s, with the farmers’ alliance against the Gold Standard, bankers and financiers.

The author moves on to analyze the effects of trade on redistribution. Based on the theorem developed by Stolper and Samuelson (1941), Rodrik argues that in most international economic models where trade does not lead to specialization, “there is always at least one factor of production that is rendered worse off by the liberalization of trade. In other words, trade generically produces losers”. Moreover, he argues that the net profits of trade openness decrease relatively to the redistribution costs, as the initial barriers to trade are lower. He backs this argument with empirical evidence from the literature on NAFTA and the US trade with China, and a model that looks at the effect of the size of the initial tariff being removed on the change in low-skill wages and the increase in real income of the economy.

Rodrik also argues that although there could be a form of compensation for the affected industries, this is usually very costly and not practical. Also, one of the reasons why populist movements in Europe have not been anti-trade might be the existence of safety nets that made unnecessary ex-post mechanisms of compensation. Very important as well is the general perception of the masses on the degree of fairness of the increase in inequality perceived after reducing trade tariffs. Namely, populism is more likely to appear when the losses derived from globalization and increases in inequality are deemed to be produced by a group taking unfair advantage of the new economic atmosphere.

The author also analyzes the perils of financial globalization, whereby looking at the current literature of the effects of capital mobility on inequality, he concludes that countries prefer when capital adopts the form of a long-term flow, like direct foreign investment, rather than short-term, volatile financial flows. Rodrik comments that the literature has found that financial globalization tends to increase the negative impact of low-quality domestic institutions. There is also a high correlation presented by Reinhart and Rogoff (2009) between capital mobility and the incidence of banking crises.

The article concludes with an analysis of the possible determinants of the specific type of populism that spreads in a given country. In a different paper (Mukand and Rodrik, 2017) Rodrik presented a model that could explain to some extent the reason why populist movements in Europe have traditionally been right winged, whereas in Latin America they have been usually left winged. The main determinants in the model were the presence of an ethno-national/cultural or an income/social cleavage. Rodrik also provides empirical evidence of this phenomenon with a newly constructed dataset.

Comments

During my training as an economist I was well aware of the distributional effects that trade has on the economies involved. Nonetheless, the argument I heard was always that trade is a positive-sum game and net profits from it could be redistributed among the losers, thus alleviating any negative effects. The usual argument to explain why trade openness was sometimes not so popular was that the potential losers from trade were better represented and had more lobbying power, thus preventing tariff reductions. As Rodrik argues in this paper, sometimes, especially at advanced stages of globalization, not only are there problems redistributing the potential net profits; it looks as the net effects of opening more the economy at this stage might be actually negative.

This paper comes out at a moment when academics, politicians, the media, and the general public are trying to understand the reasons why these movements have appeared somewhat all of a sudden. Rodrik’s argument is that these events were predictable. The implications of the development of a particular form of populism on economic welfare are still not clear yet: analyzing this could be one of the lines of future research opened by this paper. Very often populism is associated with demagoguery, and it will be very important to differentiate between the two in the future. It is not the same that an anti-corrupt-establishment movement aims to change the political structure of a country, than filling the public opinion with lies and false promises as it happened with Brexit in the UK and with the peace treaty referendum in Colombia. In the former, the Leave campaign promised to the general public that the resources spent on the EU could be directly transferred to funding the National Health Service, which turned out to be a false statement. In the latter, leaks of recordings from the campaign opposing the peace treaty clearly showed how different socio-economic groups were fed different false arguments to gain their sympathy.

Finally, the paper shows the relevance of economic history for the discussion of present problems. Rodrik uses economic history to acknowledge that populism has sprung in the past at advanced stages of globalization. Following his example, economic historians should contribute to the literature by further explaining the channels through which populism has developed, to help us understand which are the consequences of different types of populism on economic development and societal welfare.

Abstract: The fall of labor’s share of GDP in the United States and many other countries in recent decades is well documented but its causes remain uncertain. Existing empirical assessments of trends in labor’s share typically have relied on industry or macro data, obscuring heterogeneity among firms. In this paper, we analyze micro panel data from the U.S. Economic Census since 1982 and international sources and document empirical patterns to assess a new interpretation of the fall in the labor share based on the rise of “superstar firms.” If globalization or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labor in firm value-added and sales. As the importance of superstar firms increases, the aggregate labor share will tend to fall. Our hypothesis offers several testable predictions: industry sales will increasingly concentrate in a small number of firms; industries where concentration rises most will have the largest declines in the labor share; the fall in the labor share will be driven largely by between-firm reallocation rather than (primarily) a fall in the unweighted mean labor share within firms; the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; and finally, such patterns will be observed not only in U.S. firms, but also internationally. We find support for all of these predictions.

In the last few years, inequality has been at the center of many political and academic debates. It turns out that, although less mentioned in these debates, the rapid growth of some developing countries in the last decades has actually decreased global inequality. But then, why is there a big debate about inequality? The issue is that, on the other hand, inequality in developed countries has been increasing over time. From the perspective of the functional distribution of income between labor and capital, one of the indicators of this increase in inequality is that the labor’s share of GDP has been falling in the United States and other countries in recent decades. These forces have generated winners and losers. As economist Branko Milanovic points out with his famous “elephant chart,” the middle class of the world and the very rich of the world are the two groups whose incomes have increased more rapidly. In contrast, it can be easily seen that there are large groups of people uncomfortable with increased inequality. Moreover, the factors assumed to be causing inequality have taken a vital role in political debates and recent elections.

“Elephant Chart”: Lakner & Milanovic (2016)

In this context, it is extremely important to understand what is driving these changes in inequality. There are different approaches to understand the increase in inequality in developed countries. The two main perspectives point to the importance of top incomes and changes in the tax system (e.g. Piketty and Saez, 2014), on one hand, and to changes in the labor market, mainly related to the incorporation of technological change that is more favorable to skilled workers (e.g. Autor, 2014), on the other. More recent approaches have begun to more directly incorporate the role of firms. For example, a growing literature estimates models to separate the firm’s and employee’s contributions to wage differences via double fixed-effects models, with many studies finding that firm wage effects account for approximately 20% of the overall variance of wages and have had an increasingly important role over time (e.g. Card et al., 2016). However, while we can all see that “superstar firms” like Apple, Microsoft, Google or many others in different sectors of the economy are growing very quickly, we still do not know what their effect of inequality is.

Do these “superstar firms” increase inequality because they are responsible for the decrease in labor’s share? The paper by Autor, Dorn, Katz, Patterson and Van Reenen addresses exactly this issue. If we are interested in understanding the role of firms in the increase in inequality, it is particularly important to answer the question of whether the decrease in labor’s share of income can be explained by technological changes occurring within firms, or if it is better explained by a rise of “superstar” firms, which tend to use new technologies and are more capital-intensive. The main argument of the authors is that markets have changed in such a way that firms with superior quality, lower costs, or greater innovation get disproportionately high rewards relative to previous periods. Since these “superstar firms” have higher profit levels, they also tend to have a lower share of labor in sales and value-added. Therefore, as these firms gain market share across a wide range of sectors, the aggregate share of labor falls. In this way, “superstar firms” are one of the drivers of the decrease in labor’s share (in favor of capital’s share) of value added.

Before they start developing the evidence for this argument, the authors clearly document the fall in labor’s share of GDP in the United States and other developed countries. After that, they formalize their main argument in a model of “superstar firms,” in order to derive the set of predictions that will be taken to the data. With this model in hand, the authors use several sources of information (U.S. Economic Census, KLEMS, UN Comtrade Database, and others) to run a series of regressions and decompositions to analyze the testable predictions of the model. First, the authors find that sales concentration levels have risen in most sectors. Second, they show that the larger decreases in labor’s share are observed in industries where concentration has increased the most. Third, by comparing the weighted and unweighted mean of labor’s share, the authors conclude that the fall in labor’s share has an important component of reallocation between (and not within) firms. Furthermore, they find that the between-firm reallocation of labor’s share is greatest in the sectors that are concentrating the most. Finally, these patterns are not only present in the US but also in many European countries.

Overall, all of these findings are consistent with the idea of a rise of “superstar firms” that have lower labor’s share, and which have gained more importance by concentrating large shares of sales in different sectors of the economy. It should be noted, however, that the authors do not provide a clean causal identification of the superstar firm model. The empirical exercises are done carefully and controlling for the factors that can more clearly affect the tested relationships. The use of fixed effects and trends by industry allow the authors to obtain identification exclusively from the acceleration or deceleration of labor’s shares and concentration conditional on these controlled trends. Thus, any potential threat to this identification strategy would have to come from other factors not captured by these trends or fixed effects and which are correlated with industry concentration and inequality.

This paper makes a major contribution by pointing out the role of “superstar firms” in explaining increasing inequality and opens some avenues for future research in a direction that had not been typically considered in the literature. In this sense, a particularly interesting direction would be to use the matched employer-employee databases with census data on sales to test if industry concentration has impacts on the firm component of wages and the within and between firm decomposition in each sector.

Finally, the paper addresses the question of what is the driver of the growth of these “superstar firms.” The main debate here is whether the rise of these “superstar firms” and industry concentration are associated with competitive forces, or if they are a signal of an economy with competition problems. Increased concentration can be a result of technological changes: some sectors could be introducing technologies that have a “winner takes all” aspect. An alternative, more worrisome story is that leading firms are less exposed to competition because they can create barriers to entry or have more lobbying power. The authors provide evidence that is somewhat comforting about this point. They show that concentration is greater in industries experiencing faster technical change, approximated either by patent activity or by total factor productivity growth. However, this evidence is still subject to debate. It could be the case that these originally innovative firms are now using their market power to generate barriers to entry. This can be even more important in some technology sectors where network effects generate an important advantage to the innovators. I think this discussion is actually one of the main directions where this stream of research can be expanded and complemented in the future. In this sense, for example, sector-specific partial equilibrium models could allow formalizing the product and labor markets under innovation dynamics, and such models could be estimated using data for specific industries and structural econometrics estimation techniques.

To sum up, I think that this paper makes a major contribution by pointing out the effect of “superstar firms” on the decrease of labor’s share of GDP, and therefore increased inequality in developed countries. Additionally, this paper opens several avenues for future work in order to generate more evidence consistent with the “superstar firms” model and, critically, to understand its causes and consequences at the individual micro level, especially using matched individual and firm level databases and sector-specific analysis. To understand the relationship between firms and inequality is a key task in a world of “superstar firms,” and these are key inputs for the discussion of, for example, the roles of tax policies, labor market institutions and their relationship with the increasing heterogeneity of firms.

Abstract: Despite the large increase in U.S. income inequality, consumption for families at the 25th and 50th percentiles of income has grown steadily over the time period 1960-2015. The number of cars per household with below median income has doubled since 1980 and the number of bedrooms per household has grown 10 percent despite decreases in household size. The finding of zero growth in American real wages since the 1970s is driven in part by the choice of the CPI-U as the price deflator; small biases in any price deflator compound over long periods of time. Using a different deflator such as the Personal Consumption Expenditures index (PCE) yields modest growth in real wages and in median household incomes throughout the time period. Accounting for the Hamilton (1998) and Costa (2001) estimates of CPI bias yields estimated wage growth of 1 percent per year during 1975-2015. Meaningful growth in consumption for below median income families has occurred even in a prolonged period of increasing income inequality, increasing consumption inequality and a decreasing share of national income accruing to labor.

Contrary to the popular outcry that the gap between rich and poor in the United States has steadily increased since the 1960s and that the quality of life has steadily deteriorated, Bruce Sacerdote argues that the picture is not as grim and that the steady rise of household consumption for households “with below median income” is evidence that the national economy has continued to thrive for all U.S. citizens and not just those on the top.[1] In “Fifty Years of Growth in American Consumption, Income, and Wages” Sacerdote reveals that the focus on wage growth favored by economists and policy makers impedes us from focusing on other aspects of growth, such as consumption and the quality of consumed goods.[2] From his perspective focusing on real wage growth and the inflated rates of the Consumer Price Index (CPI) only tells half of the story and that it is therefore necessary to center on consumption data in order to construct a more holistic picture of the economic realities of the below median income household.[3] From his perspective, “low income families have seen important gains in at least some areas of consumption” thanks in part to a steady growth in consumption of 1.7 percent per year since 1960.[4]

Bruce Sacerdote adjusted the CPI to the bias corrections developed by Dora Costa and Bruce Hamilton who previously worked on similar questions, looking at “the true costs of living” and new ways of estimating “real incomes” in the United States.[5] His findings for the period between 1960 to 2015 concluded that there was an increase of 164 percent in consumption for those below the median household income.[6] A previous consumption measure for the same period of time, excluding the bias measures from Costa and Hamilton, showed a 62 percent increase in consumption.[7] A third measurement that calculated real wages using the Federal Reserve’s Personal Consumption Expenditures (PCE) for the same period of time reversed the claims of wage stagnation furthered by some economists, policy makers, citizens, and labor union advocacy groups. This last measurement showed that when using the PCE to deflate nominal wages, the growth of real wages was 0.54 percent per year.[8] This contradicts the arguments of data sets such as the “2016 Distressed Community Index” that focus specifically on the increasing gap between rich and poor in the United States.[9]

Beside the bias corrections and other measurements, Sacerdote argues that the quality, technology, and durability of current consumption goods is superior to that of previous decades, therefore expanding the relative capacity of consumption of those below the median income. For example he claims that “the number of cars per household has risen from 1 to 1.6 during 1970-2015,” while the median home square footage for this income segment has risen about 8 percent during this same period of time.[10]

His objective of focusing “on growth rates in consumption instead of changes in poverty rates” is achieved by using data and methodologies for analyzing data that shows that “the glass half full” but as it is evident from the working paper, quantitative data can be tailored to fit the researcher’s agenda. Numerous questions surface regarding consumption trends in the United States that lead to further conclusions that indicate that the 164 percent increase of the past fifty-plus years is the result of greater household debt and cheaper consumer goods prices that are tied to the impacts of globalization. Consumer households that fall below the median income continue to steadily consume more, there is not doubt about that, but their wages continue to depreciate while their debt continues to rise. Moreover, globalization has allowed companies to transfer their production overseas, leading to a loss of jobs in the manufacturing sector that potentially offered higher than minimum wage salaries to those households that ranked below the median income. The transfer of production has at the same time guaranteed cheaper products to these consumers that then are able to consume more with their lower wages and their greater access to loans that artificially maintain their consumption capacity while increasing their debt to income ratio.

According to the U.S. Census Bureau, the median household income for the year 2014 was $53,719.[11] This means that half of Americans earned less than that amount. This population, that represents the central focus of Sacerdote’s research, currently has an average household debt of $130,000 (assuming that those earning below the median income are forced to go into debt to maintain their standard of living).[12] The breakdown of this debt shows that mortgages, credit cards, auto loans, and student loans make up most of the American debt.[13] This could indicate that the steady consumption increase demonstrated by Sacerdote could actually be artificially maintained by the financial system that keeps the American consumer afloat.

Sacerdote’s work could also benefit from qualitative research that would provide more in-depth analysis and at the same time counter-balance his claims on consumer choice and the reliability of products being consumed. Qualitative research could provide a different explanation as to why low-income consumers have opted to hold on to their vehicles for longer periods of time, how they are able to purchase expensive technology such as cell phones and access services such as internet and cable television, if indoor plumbing is a sign of a higher quality of life or simply a response to policy and the standardization of construction norms, and if the increase in housing square footage per household really represents a higher quality of life.

Selectivity of data and research approach in this case clearly benefits the researcher’s argument but this could quickly be turned around with other sets of data and a different research approach. A focus on credit rates and debt rates over the same period of time shifts the argument around and leads to completely different conclusions, and so would a qualitative analysis of the quality of life of Americans. Although controversial, Sacerdote’s work forces the reader to think more critically about the changes that have taken place in American society in the past fifty-plus years and brings up the question of whether or not this consumption approach is more reflective of the nation’s economic dependence on consumer consumption as a percentage of the GDP.

References

[1] See for example Thomas Piketty’s argument on the increasing gap between rich and poor and the possible threat to capitalism and democratic stability in “Capital in the 21st Century.” Cambridge: Harvard University (2014).

[2] Bruce Sacerdote. “Fifty Years of Growth in American Consumption, Income, and Wages.” National Bureau of Economic Research, working paper series, working paper 23292, March 2017. Accessed April 25, 2017. http://nber.org/papers/w23292, 2.

[5] See Dora L. Costa. “Estimating Real Income in the United States from 1888 to 1994: Correcting CPI Bias Using Engel Curves.” Journal of Political Economy 109, no. 6 (2001): 1288-1310, and Bruce W. Hamilton. “The True Cost of Living: 1974-1991.” Working paper in Economics, The John Hopkins University Department of Economics, January 1998.

[6] Sacerdote. “Fifty Years of Growth in American Consumption, Income, and Wages,” 2.

Abstract: Social democracy and market liberalism offered different solutions to the same problem: how to provide for life-cycle dependency. Social democracy makes lateral transfers from producers to dependents by means of progressive taxation. Market liberalism uses financial markets to transfer financial entitlement over time. Social democracy came up against the limits of public expenditure in the 1970s. The ‘market turn’ from social democracy to market liberalism was enabled by easy credit in the 1980s. Much of this was absorbed into homeownership, which attracted majorities of households (and voters) in the developed world. Early movers did well, but easy credit eventually drove house prices beyond the reach of younger cohorts. Debt service diminished effective demand, which instigated financial instability. Both social democracy and market liberalism are in crisis.

Review by: Sergio Castellanos-Gamboa, Bangor University

Summary

This paper emerged from Avner Offer’s Tawney Lecture at the Economic History Society’s annual conference, Cambridge, 3 April 2016 (the video of which can be found here).

In this paper Offer discussed two macroeconomic innovations of the 20th century, which he calls “the market turn”. These are the changes in fiscal policy and financialisation that encompassed the shift from social democracy to market liberalism from the 1970s onwards. Social democracy is understood as a fiscal innovation which resulted in the doubling of public expenditure (from aprox. 25 to 50 per cent of GDP between 1920 and 1980). Its aim was reducing wealth inequality. Market liberalism encompassed a monetary innovation, namely the deregulation of credit which allowed households to increase their indebtedness from around 50 to 150 per cent of personal disposable income, mainly for the purpose of home ownership. According to Offer the end result of market liberalism was increasing wealth inequality. See Offer’s depiction of this process in the graph below.

Two macroeconomic financial innovations in the 20th century, UK calibration.(Note: Diffusion curves are schematic, not descriptive.)

Offer considers that both social democracy and market liberalism are norms captured by the single concept of a “Just World Theory” (Offer & Söderberg, 2016).The ideals behind social democracy are said to be supported by ideas found in classical economics, while the ideals behind market liberalism are said to have emerged from a redefinition of the origins and nature of economic value found in neoclassical economics. Contrasting the ideas behind social democracy and market liberalism brings about questions such as:

Where does value come from?,

Is it from production or is it from personal preferences and demand for the good/service?,

What is just and fair?,

What do we as individuals deserve as reward?, and

Is there really a trade-off between equality and efficiency?

Answering any of these question is not simple and heated debates abound around them. Offer, however, rescues the idea of life-cycle dependency, where the situation of the most vulnerable individuals is alleviated through collective risk pooling rather than financial markets. According to Offer, life-cycle dependency was the dominant approach to reducing poverty in most developed countries until the oil crisis of the early 1970s. Then collapse of the Bretton Woods accord that followed, led to the liberalization of credit by removing previous constraints. This in turn resulted in the “market turn”.

Offer then turns to analyse the events after the collapse of Bretton Woods that led to the increase of household indebtedness while focusing on the UK. The 1970s was a very volatile decade for Britain. For instance, oil price increases and the secondary banking crises of 1973 resulted in the highest annual increase of the inflation rate on record. Offer argues, while citing John Fforde (Executive Director of the Bank of England at that time), that the Competition and Credit Control Act 1971 was as a leap of faith in the pursuit of greater efficiency in financial markets. This Act was accompanied by a new monetary policy where changes in interest rates (the price of money) by the central bank was to bring about the control of the quantity of money. Perhaps unexpectedly and probably due to a lack of a better understanding of the origins of money, that was not the case. Previously lifted credit restrictions had to be reinstated.

Credit controls were again lifted in the 1980s. This time policy innovations went further by allowing clearing (ie commercial) banks to re-enter the personal mortgage market. The Building Societies Act 1986 allowed building societies to offer personal loans and current accounts as well as opened a pathway for them to become commercial banks (which many did after 1989 and all those societies that converted either collapsed or were taken over by clearing banks or both). Initially and up to the crash of house prices in September, 1992, personal mortgage credit grew continuously and to levels never seen before in the UK. According to Offer, during this period both political parties supported the idea of homeownership and incentivised it through programs like “Help to Buy”. However, the rise in the demand for housing combined with the stagnation in the supply of dwellings pushed up house prices, making it more difficult for first-time buyers to become homeowners. Additionally, according to Offer, the wave of easy credit of the 1980s brought with it an increase in wealth inequality and an increase in the fragility of the financial system. As debt repayments grew as proportion of income, consumption was driven down, with subsequent effects on production and services. On this Offer opined:

“In the quest for economic security, the best personal strategy is to be rich.” (p. 17)

The paper ends with possible and desirable futures for public policy initiatives to deal with today’s challenges around wealth inequality and mounting personal credit. He argues that personal debt should be reduced through rising inflation, a policy driven write-off or a combination of both. He also argues to reinstate a regime where credit is rationed. He states that financial institutions should not have the ability to create money and therefore the housing market funding should return to the old model of building societies. He has a clear preference for social democracy over market liberalism and as such argues that austerity should end, since it is having the exact opposite effects to what was intended.

Brief Comment

Offer’s thought provoking ideas comes at a time when several political and economic events are taking place (e.g. Brexit, Trump’s attack on Dodd-Frank, etc.) which, together, could be of the magnitude as “the market turn”. Once again economic historians could help better inform the debate. Citing R. H. Tawney, Offer opened the lecture (rather than the paper) by stating that:

“to be an effective advocate in the present, you need a correct and impartial understanding of the past.”

Offer clearly fulfils the latter, even though some orthodox economists might disagree with his inflationary and credit control proposals. As per usual his idea are a great contribution to the debate around market efficiency in a time when the world seems to be in constant distress. Perhaps we ought to generate more and better research to understand the mechanisms through which market liberalism generated the current levels of wealth inequality and financial instability that Offer describes. More importantly though, is analysing if social democracy can bring inequality down as it did in the past. In my view, however, in a world where productivity seems to be stagnated, real wages are decreasing, and debt keeps growing, it is highly unlikely that the public sector can produce the recipe that will set us in the path of economic prosperity for all.

Additional References

Offer, A., & Söderberg, G. (2016). The Nobel Factor: The Prize in Economics, Social Democracy, and the Market Turn. Princeton University Press.
(Read an excellent review of this book here)

Abstract: Using the newly expanded set of 40 social tables from pre-modern societies, the paper tries to find out the factors associated with the level of inequality and the inequality extraction ratio (how close to the maximum inequality have the elites pushed the actual inequality). We find strong evidence that elites in colonies were more extractive, and that more densely populated countries exhibited lower extraction ratios. We propose several possibilities linking high population density to low inequality and to low elite extraction.

Guido Alfani (Bocconi University, Milan)

Given the recent increase in the availability of good-quality data on pre-industrial (or pre-modern) societies, there is much need for works of synthesis aimed at discovering the factors shaping long-term inequality trends. Branko Milanovic has been particularly active in this field, with the publication of a recent book on Global Inequality: A New Approach for the Age of Globalization (2016, Harvard University Press) [see the reviews here – Ed]. In this new working paper, Milanovic tries to move forward, using a large database of social tables to single out the potential causes of differences in historical inequality levels and in inequality extraction. He focuses in particular on institutional factors (inequality in colonies vs other areas) and on demographic factors (population density). The results are very interesting and represent a useful step forward in our understanding of inequality change in preindustrial societies.

Summary
This paper was distributed by NEP-HIS on 2016-11-13. It makes use of a relatively large collection of social tables for preindustrial societies, including overall 40 social tables for about 30 distinct countries/world areas over a very long time: from Athens in 330 BCE to British India in 1938. As is well known, social tables allow us to roughly estimate income inequality. They are particularly useful in situations of relative scarcity of data and although they have been in use for centuries – the first example is Gregory King’s social table dating 1688 – many new ones have recently been produced for a variety of preindustrial societies across the world (see Lindert and Williamson 2016 for the U.S., Saito 2015 for Japan, Broadberry et al. 2015 for England, and Alfani and Tadei 2017 for Ivory Coast, Senegal and the Central African Republic). Although estimating complete distributions is the better option (see for example the accurate reconstruction of income distribution in Old Castile around 1750 by Nicolini and Ramos 2016, the impressive work by Reis 2017 on Portugal from 1565 to 1770, and finally, the estimates of wealth inequality in the period 1300-1800 produced by the EINITE project for a variety of Italian pre-unification states and other European areas: Alfani (2015, 2017); Alfani and Ryckbosch (2016); Alfani and Ammannati (2017), this is not always possible or feasible and social tables must be considered a good alternative especially when there is a relative scarcity of data.

As rightly argued by Milanovic, the recent accumulation of new evidence has not been accompanied by equal advances in the work on causal factors driving inequality change in preindustrial times. The seminal article by Van Zanden (1995), in which long-term inequality growth in the Dutch Republic was explained by long-term economic growth, has later been nuanced by works demonstrating that during the early modern period, in many parts of Europe inequality grew also in phases of economic stagnation, or even decline (Alfani 2015; Alfani and Ryckbosch 2016). The role played by large-scale mortality crises, particularly plague epidemics, has been underlined and the Black Death of 1347-51 has been shown to be the only event able to produce large-scale and enduring inequality decline in the period from ca. 1300 to 1800 (Alfani 2015; Alfani and Ammannati 2017). In a very recent book, Scheidel (2017) has taken this line of reasoning further, arguing that all substantial declines in inequality recorded in human history are due to catastrophic events (epidemics, wars, revolutions…).

Milanovic’s aim is to find further regularities, looking for possible economic, institutional or demographic drivers of inequality change in preindustrial times. He adopts the theoretical framework of the Inequality Possibility Frontier (introduced in Milanovic, Lindert and Williamson 2011), arguing that we should focus not only on how unequal a society is, but also on how much inequality it manages to “extract” compared to the maximum inequality it could achieve given that everybody needs to reach at least the subsistence level. Hence, as an economy manages to increase the per-capita surplus produced, it also acquires a potential for becoming more unequal. A first relevant empirical finding is that colonies tend to be exceptionally extractive, especially at low levels of per-capita GDP. As Milanovic points out, this is not surprising and can be explained by colonies being more exploitative, i.e. being pushed closer to the inequality possibility frontier by rapacious elites. This is apparent when looking at inequality extraction (being a colony raises the “inequality extraction ratio” by almost 13 percent points), but not necessarily when looking at overall inequality as measured by a Gini index.

Branko Milanovic

A more novel finding is the negative correlation between population density and both inequality and inequality extraction. In fact, a “high number of people per square kilometer seems to be a strong predictor of relatively egalitarian economic outcomes” (p. 16). Explaining this empirical finding is not easy and Milanovic resorts to two conjunctures: 1) in a less extractive economy, the poor enjoy relatively good living conditions and this might lead to greater population growth; or 2) a particularly dense population might be better able to make the position of the elite/of the ruler relatively precarious, enjoying de facto some sort of control over the actions of the elite and forcing it to adopt less extractive policies. As is clear, the direction of causality is the opposite in the two explanations – which are probably to be considered not mutually exclusive. Other correlates of inequality and inequality extraction include per-capita GDP and urbanization rates, which turn out being borderline significant (per-capita GDP) or positively but non-significantly correlated (urbanization rate), coherently with what was found by other recent comparative studies (Alfani and Ryckbosch 2016; Alfani and Ammannati 2017).

Comment

Undoubtedly, Milanovic’s new article helps to fill in a real need for more comparative research on preindustrial societies. The findings, albeit provisional, are very interesting and either they provide useful confirmation of what has already been argued by others – for example about the inability of per-capita GDP to explain preindustrial inequality growth in a satisfying way– or they lead us to think along new lines, especially regarding the impact on inequality of demographic variables. In fact, as urbanization rates proved to be a far poorer explanatory variable for inequality change than we expected (see in particular Ryckbosch 2016; Alfani and Ryckbosch 2016; Alfani and Ammannati 2017), demographic factors came to be perceived as probably relevant, but also somewhat puzzling (exception made for mass-mortality events like the Black Death, whose inequality-reducing effects now stand out very clearly). Population density offers us a novel perspective and in time, might prove to be the right path to follow.

However, there is also some space for constructive criticism. A first point to underline is that, differently from what Milanovic argues, the time might not yet be ripe for the kind of definitive and encompassing comparison that he seems to have in mind. The data available is still relatively scarce, including for Europe, which is the world area that has attracted the greatest amount of recent research. Additionally, social tables, albeit easily comparable, are not perfectly comparable – for example because they can include a greatly varying number of classes/groups. In some instances, classes are very few and we have no hint at within-class inequality. These are two reasons why, as argued above, complete distributions are strictly preferable to social tables. Finally, in the current version of Milanovic’s database, for the vast majority of countries only one social table is available, whereas multiple social tables for the same country at different time points would make for sounder statistical analyses. There are ongoing projects, especially EINITE and related projects, whose aim is to provide comparable state-level information on wealth and income inequality for large areas of the world at different points in time in the long run of history, but these projects are heavily dependent on new archival research and require time to be completed.

Secondly there are other possible common factors shaping long-term inequality change which Milanovic cannot consider in the context of the current article. Some of these have been underlined by a recent comparative paper by Alfani and Ryckbosch (2016) which, although focusing on “only” four European states during 1500-1800, nevertheless had the advantage of having recourse to inequality measures produced with a common methodology and covering all states continuously in time. This study underlined two factors common to all the areas covered: 1) “proletarianization”, i.e. the progressive disappearance of small peasant ownership, which occurred throughout Europe during the early modern period, and 2) the inequality-increasing consequences of the rise of the fiscal-military states from ca. 1500. These factors might have played a role also in other world areas, from the broader Mediterranean to East Asia and maybe elsewhere – but at present that is no more than speculation.

Obviously, such criticism in no way negates the considerable usefulness of Milanovic’s new paper – which is also a further demonstration of how his relatively new concept of the inequality possibility frontier allows for a deeper understanding of the actual conditions and consequences of distribution. It does, however, indicate that we are still a long way from being able to identify without ambiguity the main causes of inequality change in preindustrial societies that so many international economic historians are now attempting to discover.

Abstract: In this new working paper on preindustrial inequality, Nicolini and Ramos Palencia build upon their earlier work on income inequality in eighteenth-century Old Castile (Nicolini and Ramos Palencia 2015) by looking into one particularly important, and difficult to assess, aspect: how to reconstruct, for a given preindustrial society, estimates of both income and wealth inequality – considering that the sources, according to the place and the period, have the tendency to inform us only about one of the two. Given the amount of new information about long-term trends in preindustrial inequality, of either income or wealth, which has been made available by recent research, the authors point at what clearly constitutes one of the next steps we should take and in doing so, they also provide a useful contribution to the methodological debates which are taking place among scholars working on preindustrial inequality.

Review by Guido Alfani

Summary

In this paper Nicolini and Ramos explore the connection between income and wealth for a large sample of communities from different Spanish provinces: Palencia, Madrid, Guadalajara and Granada. They combine information from two different sources:

1. the Catastro de Ensenada (ca. 1750), which provides information about household income, and

2. probate inventories (covering the period 1753-68), a source which has often been used to estimate wealth inequality.

These two sources are combined using nominative linkage techniques in order to take advantages of one to solve the weaknesses of the other. In particular, the almost-universal scope of the survey within the Cadastre enables Nicolini and Ramos to assess with certain precision the actual coverage of the probate inventories (which tend to be biased towards the upper part of the distribution). This allows them the resampling or weighthing of the information to improve the study of wealth inequality. It should be underlined that the Catastro de Ensenada is a truly exceptional source. It was an early attempt at introducing a universal tax on income. As the new tax was proportional and should have replaced a number of indirect provincial taxes with regressive effects, this fiscal innovation clearly moved in the direction of a more equitable system of taxation. Unfortunately, the new tax was never implemented – but at the very least, the attempt to introduce it generated a vast amount of useful information.

Nicolini and Ramos were able to reconstruct both income and wealth for 194 observations, out of the much larger sample of 6,214 households for which they only have information about income. Nicolini and Ramos then explore the connection between income and wealth, finding (as was expected) a very strong correlation. However, they go much deeper, thanks to an econometric approach in which the distortions in the sample (determined in particular by over-representation of rich households) are corrected by weighting. They obtain many interesting and potentially useful results, in particular:

they estimate the average rate of return to wealth to be 2.9% p.a. – which is, generally speaking, much smaller that usually implied in the literature. For instance, the rate of return to wealth implied by Lindert in his work on the Florentine Cadastre of 1427 was 7% p.a. (see below). However, if the association between income and wealth is analyzed by considering their logarithm (which is the econometric specification preferred by Nicolini and Ramos), then the elasticity of income to wealth varies between 0.4 and 0.9 depending on the region. This means that a 10% increase in household wealth is associated to an income increase comprised in the 4-9% range. This range is consistent with empirical findings in many studies of past and present societies, all of which suggest that income inequality is lower than wealth inequality;

the distribution of household income increases less steeply than the distribution of household wealth. This might be due to the fact that labour income is relatively larger in the bottom part of the distribution, or that the wealth of the bottom part of the distribution consists for a larger part of income-producing assets, while the wealth of the richest people would consist also of other assets, including (unproductive) status goods and luxuries as well as cash;

the relationship between wealth and income differs depending on the sector of activity of the household head (primary vs secondary/tertiary) and on the place of residence – although somewhat surprisingly, and differently from what reported for other European regions (for example Tuscany by Alfani and Ammannati 2014), Nicolini and Ramos do not find that urban households had greater wealth than rural ones. In the study by Nicolini and Ramos urban and rural wealth were usually on par, but in the extreme case of Guadalajara urban dwellers were less wealthy than rural dwellers.

Sample of Catastro de Ensenada (Archivo Simancas)

Comment

This paper makes many interesting and potentially important contributions to the study of inequality in the early modern period, a field which has been particularly fertile in recent years. First, it provides new information about inequality in the Iberian peninsula, integrating other recent studies (e.g. Santiago-Caballero 2011; Reis and Martins 2012). Secondly, it contributes considerably to the development of a methodology to translate in a non-arbitrary way income distributions into wealth distributions, and vice versa. This is a crucial point, which deserves some attention.

The Ensenada Cadastre is an exceptional source as it provides data on income. As a matter of fact, most other sources of the “cadastrial” kind are essentially property tax records, which always list real estate and sometimes other components of wealth – but not income. However, it has also been argued that for the preindustrial period, in most instances wealth distributions are the best proxy we have for income distributions (Lindert 2014; Alfani 2015). This being said, moving from the good-quality distributions of wealth that have recently been made available for different parts of late medieval and early modern Europe (in particular, Alfani 2015; Alfani and Ryckbosch 2015) to acceptable distributions of income is clearly a worthy pursuit.

I would differ with Nicolini and Ramos Palencia in their statement that theirs is the first attempt at studying together income and wealth distributions in the pre-industrial period. For example, Soltow and Van Zanden (1998) did so in their study of the Netherlands. However, Nicolini and Ramos do provide useful and interesting insights into how to convert wealth distributions into income distributions. Many such attempts are currently underway and there are earlier examples, like Lindert’s method to convert the distribution of wealth in the 1427 Florentine catasto into an income distribution (results used in Milanovic, Lindert and Williamson 2011).

Moreover, Nicolini and Ramos Palencia stress many potential pitfalls in procedures of this kind. This being said, there are aspects of their current reconstructions which are a bit surprising and might be the result of sampling issues, as 59% of the 194 observations relate to the province of Palencia. Is Guadalajara, where rural dwellers were wealthier than urban dwellers, an exceptional case or does this depend on the very small sample (just 12 observations) the authors have for that region? To dispel any doubts, more probate inventories should be collected, in order to improve the territorial balance within the sample and to better account, both in the estimation process and in the econometric analysis, for possible regional variations. However, this does not alter the general conclusion. The paper by Nicolini and Ramos is a very useful piece of innovative research, grounded in new archival data and packed with useful insights about how to improve our knowledge of inequality in the pre-industrial period.

Ferdinand VI (1713 – 1759), called the Learned, was King of Spain from 9 July 1746 until his death.

Nicolini, E.A. and F. Ramos Palencia (2015), “Decomposing income inequality in a backward pre-industrial economy: Old Castile (Spain) in the middle of the eighteenth century”, The Economic History Review, online-first version, DOI: 10.1111/ehr.12122.

Reis, J., Martins, A. (2012), “Inequality in Early Modern Europe: The “Strange” Case of Portugal, 1550-1770”. Paper given at the conference Wellbeing and Inequality in the Long Run (Madrid, 1 June 2012).